Capitalizing on machine learning—from life sciences to financial services

December 26, 2016

The promise of machine learning has a science fiction flavor to it: computer programs that learn from their experiences and get better and better at what they do. So is machine learning fact or fiction?

The global marketplace answers this question emphatically: Machine learning is not just real; it is a booming field of technology that is being applied in countless artificial intelligence (AI) applications, ranging from crop monitoring and drug development to fraud detection and autonomous vehicles. Collectively, the global AI market is expected to be worth more than $16 billion by 2022, according to the research firm MarketsandMarkets.[1]

In the life sciences arena, researchers are leveraging machine learning in their work to drive groundbreaking discoveries that may help improve the health and wellbeing of people. This research is taking place around the world.

In the United States, for example, researchers at the MIT Lincoln Laboratory Supercomputing Center (LLSC) are applying the power of machine learning algorithms and a new Dell EMC Top500 supercomputer to ferret out patterns in massive amounts of patient data collected from publicly available sources. These scientific investigations could potentially lead to faster personalized treatments and the discovery of cures.

In one such project, researchers affiliated with the LLSC used the new Top500 supercomputer to gain insights from an enormous amount of data collected from an intensive care unit over 10 years. “We did analytics and analysis on this data that was not possible before,” says LLSC researcher Vijay Gadepally. “We were able to reduce two to 10 times the amount of time taken to do analysis, such as finding patients who have similar waveforms.” Watch the video.

In China, Dell EMC is collaborating with the Chinese Academy of Sciences on a joint artificial intelligence and advanced computing laboratory. This lab focuses on research and applications of new computing architectures in the fields of brain information processing and artificial intelligence. Research conducted in the lab spans cognitive function simulation, deep learning, brain computer simulation, and related new computing systems. The lab also supports the development of brain science and intellect technology research, promoting Chinese innovation and breakthroughs at the forefront of science. In fact, Dell China was recently honored with an “Innovation Award of Artificial Intelligence in Technology & Practice” award in recognition of the collaboration. Read the blog.

In Europe, meanwhile, the University of Pisa is using deep learning technologies and systems from Dell EMC for DNA sequencing, encoding DNA as an image. The examples like these could go on and on, because the application of machine learning techniques in the life sciences has tremendous momentum in laboratories around the world.

So why does this matter? In short, because we need to gain insights from massive amounts of data, and this process requires systems that exceed human capabilities. Machine learning algorithms can dig through mountains of data to ferret patterns that might not otherwise be recognizable. Moreover, machine learning algorithms get better over time, because they learn from their experiences.

In the healthcare arena, machine learning promises to drive life-saving advances in patient care. “While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care,” notes author Bernard Marr, writing in Forbes. “Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care.”[2]

Machine learning is also making wide inroads in diverse industries and commercial applications. MasterCard, for example, is using machine learning to detect fraud, while Facebook is putting machine learning technologies to work via a facial recognition algorithm that continually improves its performance. Watch the video.

“Machine learning has become extremely popular,” says Jeremy Kepner, Laboratory Fellow and head of the MIT Lincoln Laboratory Supercomputing Center. “Computers can see now. That’s something that I could not say five years ago. That technology is now being applied everywhere. It’s so much easier when you can point a camera at something and it can then produce an output of all the things that were in that image.” Watch the video.

Here’s the bottom line: Machine learning is no longer the stuff of science fiction. It’s very real, it’s here today and it’s getting better all the time—in life sciences and fields beyond.

Ready to get started with machine learning?

Here are some ways to further your understanding of what machine learning systems could do for your organization:

  • Many courses available in machine learning.
  • A growing number of open source communities are driving advances in machine learning. You can find links to communities and other resources in the Intel Developer Zone.
  • Dell EMC | Intel HPC Innovation Centers around the world offer opportunities for technical collaboration and early access to technology.

 

[1] MarketsandMarkets. “Artificial Intelligence Market by Technology (Deep Learning, Robotics, Digital Personal Assistant, Querying Method, Natural Language Processing, Context Aware Processing), Offering, End-User Industry, and Geography – Global Forecast to 2022.” November 2016.

[2] Bernard Marr. “How Machine Learning, Big Data And AI Are Changing Healthcare Forever.” Forbes. Sept. 23, 2016

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

UCSD Web-based Tool Tracking CA Wildfires Generates 1.5M Views

October 16, 2017

Tracking the wildfires raging in northern CA is an unpleasant but necessary part of guiding efforts to fight the fires and safely evacuate affected residents. One such tool – Firemap – is a web-based tool developed b Read more…

By John Russell

Exascale Imperative: New Movie from HPE Makes a Compelling Case

October 13, 2017

Why is pursuing exascale computing so important? In a new video – Hewlett Packard Enterprise: Eighteen Zeros – four HPE executives, a prominent national lab HPC researcher, and HPCwire managing editor Tiffany Trader Read more…

By John Russell

HPE Extreme Performance Solutions

“Lunch & Learn” to Explore the Growing Applications of Genomic Analytics

In the digital age of medicine, healthcare providers are rapidly transforming their approach to patient care. Traditional technologies are no longer sufficient to process vast quantities of medical data (including patient histories, treatment plans, diagnostic reports, and more), challenging organizations to invest in a new style of IT to enable faster and higher-quality care. Read more…

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

OLCF’s 200 Petaflops Summit Machine Still Slated for 2018 Start-up

October 3, 2017

The Department of Energy’s planned 200 petaflops Summit computer, which is currently being installed at Oak Ridge Leadership Computing Facility, is on track t Read more…

By John Russell

US Exascale Program – Some Additional Clarity

September 28, 2017

The last time we left the Department of Energy’s exascale computing program in July, things were looking very positive. Both the U.S. House and Senate had pas Read more…

By Alex R. Larzelere

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Leading Solution Providers

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Cente Read more…

By Linda Barney

  • arrow
  • Click Here for More Headlines
  • arrow
Share This